As a EU citizen I’m at a loss for what to do about this. I feel that they’re going against any average citizen’s interest. What can we do to make them stop?
I have the feeling that this article was hurt rather than helped by being written using LLMs. It was really hard to follow, and even though I read it hoping to learn something new, I left feeling more confused than when I started. The feeling while reading was that the prose was trying to hold my hand but had absolutely no empathy for the build up of my understanding over the article. It’s a bit like when, as a child, you’d do homework with your parent and the parent would start saying “don’t you see how it’s obvious that 25/5=5” with no further explanation and a building tone of frustration.
Are there any good end-user apps that are supported on a broad set of platforms and use Iroh to support file transfers between e.g. Windows and iOS seamlessly?
Wispr Flow is a masterclass in STT. Apple's solution feels like it's from the last century in comparison. Same applies with Apple's TTS when you have ElevenLabs and OpenAI running laps around it. All I need is for my iPhone to do those things natively at the same quality level (because in Apple's walled garden that's the only way to get them usable everywhere).
Looks awesome, but I wonder if its functionality could be exposed to existing CLIs such as Claude Code instead of having to run it through its own CLI, mainly because I don't want to spend on credits when I've already got a CC subscription.
EDIT: To clarify, I realize there are skill files that can be used with Claude directly, but the snapshot analysis model seems to require a key. Any way to route that effort through Claude Code itself, such as for example exporting the raw snapshot to a file and instructing Claude Code to use a built-in subagent instead?
How is this on the front page? This reads like pure AI slop. It feels like an insult to the reader.
OP: if you thought you had something useful to say, why didn’t you write it in your own words. There’s no useful content I can discern while reading this post.
> FastRender may not be a production-ready browser, but it represents over a million lines of Rust code, written in a few weeks, that can already render real web pages to a usable degree
I feel that we continue to miss the forest for the trees. Writing (or generating) a million lines of code in Rust should not count as an achievement in and of itself. What matters is whether those lines build, function as expected (especially in edge cases) and perform decently. As far as I can tell, AI has not been demonstrated to be useful yet at those three things.
That’s not what I meant. What I’m asking is whether there’s any evidence that the latest “techniques” (such as Ralph) can actually lead to high quality results both in terms of code and end product, and if so, how.
This is exactly the issue I have with what I'm seeing around: lots of "here's something impressive we did" but nearly nothing in terms of how it was actually achieved in clear, reproducible detail.
Your point is fair, but it rests on a major assumption I'd question: that the only limit lies with the user, and the tooling itself has none. What if it’s more like “you can’t squeeze blood from a stone”? That is, agentic coding may simply have no greater potential than what I've already tried. To be fair I haven't gone all the way in trying to make it work but, even if some minor workarounds exist, the full promise being hyped might not be realistically attainable.